package com.rbt;

import com.set.FileOperation;

import java.util.ArrayList;

/**
 * 红黑树
 * （代码有BSTMap改造而来）
 * @param <K>
 * @param <V>
 */
public class RBTree<K extends Comparable<K>, V> {

    private static final boolean RED = true;
    private static final boolean BLACK = false;

    private class Node {
        public K key;
        public V value;
        public Node left;
        public Node right;
        public boolean color;

        public Node(K key, V value) {
            this.key = key;
            this.value = value;
            left = null;
            right = null;
            // 默认新节点总是某个节点融合，所以为红色
            color = RED;
        }
    }
    private Node root;
    private int size;

    public RBTree() {
        root = null;
        size = 0;
    }

    /**
     * 判断节点 node 的颜色
     * @param node
     * @return
     */
    private boolean isRed(Node node) {
        if (node == null) {
            return BLACK;
        }
        return node.color;
    }

    /**
     * 红黑树做旋转
     *
     *        node                      x
     *        | \         左旋转       | \
     *       T1  x       ------>     node T3
     *          |\                  | \
     *         T2 T3               T1 T2
     * @param node
     * @return
     */
    private Node leftRotate(Node node) {
        Node x = node.right;

        // 做旋转
        node.right = x.left;
        x.left = node;

        x.color = node.color;
        node.color = RED;

        return x;
    }

    /**
     *
     *        node                x
     *        | \                | \
     *       x  T2    ----->    y  node
     *     | \                     | \
     *    y  T1                   T1 T2
     * 右旋转
     *
     * 临时4节点
     * @param node
     * @return
     */
    private Node rightRotate(Node node) {
        Node x = node.left;
        // 右旋转
        node.left = x.right;
        x.right = node;

        x.color = node.color;
        node.color = RED;

        return x;
    }


    /**
     * 颜色翻转
     * (在3阶节点中插入新的元素之后需要做颜色的翻转)
     * @param node
     * @return
     */
    private void flipColors(Node node) {
        node.color = RED;
        node.left.color = BLACK;
        node.right.color = BLACK;
    }



    /**
     * 向红黑树中添加新节点
     * @param key
     * @param value
     */
    public void add(K key, V value) {
        root = add(root, key, value);
        // 保持根节点为黑色
        root.color = BLACK;
    }

    /**
     * 使用递归算法向以node 为根的红黑树中添加元素，
     * 插入新节点之后返回红黑树的根
     * @param node
     * @param key
     * @param value
     * @return
     */
    private Node add(Node node, K key, V value) {
        // 递归到底就创建新的节点
        if (node == null) {
            size ++;
            // 默认是红色
            return new Node(key, value);
        }
        if (key.compareTo(node.key) < 0) {
            node.left = add(node.left, key, value);
        }else if (key.compareTo(node.key) > 0) {
            node.right = add(node.right, key, value);
        }else {
            // 如果是原来的key, 那变成更新
            node.value = value;
        }
        // 维护红黑树的性质 TODO
        if (isRed(node.right) && !isRed(node.left)) {
            node = leftRotate(node);
        }
        if (isRed(node.left) && isRed(node.left.left)) {
            node = rightRotate(node);
        }
        if (isRed(node.left) && isRed(node.right)) {
            flipColors(node);
        }
        return node;
    }


    /*public V remove(K key) {
        Node node = getNode(root, key);
        if (node != null) {
            root = remove(root, key);
            return root.value;
        }
        return null;
    }

    *//**
     * 使用递归删除以node 为根节点的二分搜索树中的节点
     * 返回删除节点之后新的二分搜索树的根
     * @param node
     * @param key
     * @return
     *//*
    private Node remove(Node node, K key) {
        if (node == null) {
            return null;
        }
        if (key.compareTo(node.key) < 0) {
            node.left = remove(node.left,key);
            return node;
        }else if (key.compareTo(node.key) > 0) {
            node.right = remove(node.right, key);
            return node;
        }else {
            // 待删除左子树为空的情况
            if (node.left == null) {
                Node rightNode = node.right;
                node.right = null;
                size --;
                return rightNode;
            }
            // 待删除右子树为空的情况
            if (node.right == null) {
                Node leftNode = node.left;
                node.left = null;
                size --;
                return leftNode;
            }
            // 待删除左右子树均不为空的情况
            Node successor = minimum(node.right);
            successor.right = removeMin(node.right);
            successor.left = node.left;
            node.right = null;
            node.left = null;
            return successor;
        }

    }

    *//**
     * 返回以node为根的二分搜索树的最小值所在的节点
     * @param node
     * @return
     *//*
    private Node minimum(Node node) {
        if (node.left == null) {
            return node;
        }
        return minimum(node.left);
    }

    *//**
     * 删除以node为根的二分搜索树中最小的节点
     * 返回删除节点后的二分搜索树的根
     * @param
     * @return
     *//*
    private Node removeMin(Node node) {
        if (node.left == null) {
            Node rightNode = node.right;
            node.right = null;
            size --;
            return rightNode;
        }
        node.left = removeMin(node.left);
        return node;
    }*/

    public boolean contains(K key) {
        return getNode(root, key) != null;
    }

    public V get(K key) {
        Node node = getNode(root, key);
        return node == null ? null: node.value;
    }

    public void set(K key, V newValue) {
        Node node = getNode(root, key);
        if (node == null) {
            throw new IllegalArgumentException(key + "doesn't exist!");
        }else {
            node.value = newValue;
        }

    }

    public int getSize() {
        return size;
    }

    public boolean isEmpty() {
        return size == 0;
    }

    /**
     * 返回以node为根节点的二分搜索树中的key所在的节点
     * @param node
     * @param key
     * @return
     */
    private Node getNode(Node node, K key) {
        if (node == null) {
            return null;
        }
        if (key.compareTo(node.key) == 0) {
            return node;
        }else if (key.compareTo(node.key) < 0) {
            return getNode(node.left, key);
        }else {
            return getNode(node.right, key);
        }
    }

    public static void main(String[] args) {
        String filePath = "E:\\WorkSpace\\LearningDemoWorkSpace\\data-structure\\src\\pride-and-prejudice.txt";
        ArrayList<String> words = new ArrayList<>();
        if (FileOperation.readFile(filePath, words)) {
            System.out.println("Total words: " + words.size());
            RBTree<String, Integer> map = new RBTree<>();
            for (String word: words) {
                if (map.contains(word)) {
                    map.set(word, map.get(word) + 1);
                } else {
                    map.add(word, 1);
                }
            }
            System.out.println("Total different words: " + map.size);
            System.out.println("Frequency of pride: " + map.get("pride"));
        }
    }
}



